Published in:
Open Access
01-12-2013 | Research article
Validation of the chronic disease score-infectious disease (CDS-ID) for the prediction of hospital-associated clostridium difficile infection (CDI) within a retrospective cohort
Authors:
Vanessa Stevens, Cathleen Concannon, Edwin van Wijngaarden, Jessina McGregor
Published in:
BMC Infectious Diseases
|
Issue 1/2013
Login to get access
Abstract
Background
Aggregate comorbidity scores are useful for summarizing risk and confounder control in studies of hospital-associated infections. The Chronic Disease Score – Infectious Diseases (CDS-ID) was developed for this purpose, but it has not been validated for use in studies of Clostridium difficile Infection (CDI). The aim of this study was to assess the discrimination, calibration and potential for confounder control of CDS-ID compared to age alone or individual comorbid conditions.
Methods
Secondary analysis of a retrospective cohort study of adult inpatients with 2 or more days of antibiotic exposure at a tertiary care facility during 2005. Logistic regression models were used to predict the development of CDI up to 60 days post-discharge. Model discrimination and calibration were assessed using the c-statistic and Hosmer-Lemeshow (HL) tests, respectively. C-statistics were compared using chi-square tests.
Results
CDI developed in 185 out of 7,792 patients. The CDS-ID was a better standalone predictor of CDI than age (c-statistic 0.653 vs 0.609, P=0.04). The best discrimination was observed when CDS-ID and age were both used to predict CDI (c-statistic 0.680). All models had acceptable calibration (P>0.05).
Conclusion
The CDS-ID is a valid tool for summarizing risk of CDI associated with comorbid conditions.